1 | initial version |

To obtain the version of the model with the "best fit"
for the parameters found by `find_fit`

, use `subs`

.

If that was not the question, can you clarify it?

Example of applying `subs`

to the result of `find_fit`

:

```
sage: R = [[0, 1], [4, 2], [8, 4], [12, 8], [16, 16],
....: [20, 32], [24, 64], [28, 128], [32, 256]]
sage: p = scatter_plot(R)
sage: a = var('a')
sage: model(x) = 2^(a*x)
sage: fit = find_fit(R, model)
sage: f(x) = model(x).subs(fit)
sage: f
x |--> 2^(0.25*x)
sage: a, b = SR.var('a, b')
sage: model(x) = a^(b*x)
sage: fit = find_fit(R, model)
sage: fit
[a == 1.1017948048163804, b == 1.7875584659241468]
sage: g(x) = model(x).subs(fit)
sage: g
x |--> 1.1017948048163804^(1.7875584659241468*x)
```

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